Traditional finite element (FE) methods used to analyze drill string dynamics are linear and operate in the frequency domain. They can address only one type of drilling problem at a time (e.g. bit-bounce, stick-slip or bending) and cannot account for coupled motions or aperiodic responses. While attempts have been made to more completely examine fully-coupled and three-dimensional bottom-hole-assembly (BHA) responses using non-linear FE methods, those efforts have proven computationally problematic for long drill strings and even for some more complex short duration simulations.
Using a multi-body dynamics (MBD) approach, drill string components are modeled in a physically intuitive manner. All nonlinear geometric and inertial effects are properly accounted for, without restrictions on angular displacements or angular rates. Modern commercial MBD codes run on typical engineering workstations and are much faster than FE simulations which are often two to three orders of magnitude slower for drill string models. The computational efficiency of MBD also enables parametric variations and sensitivity studies of BHA configuration and surface drilling controls that can help the driller optimize drilling performance and avoid dysfunctions.
Multi-body simulations are performed in the time-domain. Input parameters such as hole diameter, well trajectory, bit wear, wall stiffness, contact damping and friction, as well as operating parameters like hookload, drive torque and flow rates, can also be defined as a function of depth. Some model input and parameters may be uncertain. In such situations the efficient parametric variation capability of the MBD codes can be used to “tune” the model to match whatever surface and downhole data are available, including magnitudes, phases and frequency content.
MBD models can be extensively instrumented to predict the response along the entire length of the drill string with a very low computational cost and which can be visualized versus time. Such displays, together with graphical animations of drill string motions, provide a more complete picture than is available from other analytical approaches of what is physically happening downhole. Loads computed by the MBD simulations can be applied to more detailed FE models of drill string components to predict stress and fatigue. These physical insights enable drilling engineers to make better assessments of BHA design choices, and ultimately enable manufacturers to design better drilling tools.
Results of MBD modeling are presented that provide insights on an actual drilling dysfunction and downhole failure.
Robust and efficient MBD-based drill string modeling and simulation that reliably predict the dynamic response of the drill string and BHA prior to tripping into a well, combined with the ability to update those predictions as measured data are received from both surface and downhole, can improve bit life, reduce string failures, facilitate improvements to BHA designs and improve overall drilling performance with a significant reduction in drilling costs. Ultimately, because of its very fast solution speeds, MBD-based analysis could become a key component of drilling automation.